International journal of epidemiology最新文献

Journal peer review is a gatekeeper in the scientific process, determining which papers are published in academic journals. It also supports authors in improving their papers before they go to press. Training for early-career researchers on how to conduct a high-quality peer review is scarce, however, and there are concerns about the quality of peer review in the health sciences. Standardized training and guidance may help reviewers to improve the quality of their feedback. In this paper, we approach peer review as a staged writing activity and apply writing process best practices to help early-career researchers and others learn to create a comprehensive and respectful peer-review report. The writing stages of reading, planning and composing are reflected in our three-step peer-review process. The first step involves reading the entire manuscript to get a sense of the paper as a whole. The second step is to comprehensive evaluate the paper. The third step, of writing the review, emphasizes a respectful tone, providing feedback that motivates revision as well as balance in pointing out strengths and making suggestions. Detailed checklists that are provided in the Supplementary material (available as Supplementary data at IJE online) aid in the paper evaluation process and examples demonstrate points about writing an effective review.

Background: Despite persistent concerns about only children's disadvantage relative to individuals with siblings, existing health-related evidence is inconsistent. Recent evidence from Nordic countries about only children having poorer health outcomes may not apply elsewhere because selection processes differ across contexts. We investigate the midlife health of only children in the UK where one-child families tend to be socio-economically advantaged relative to large families.

Methods: Using the 1946, 1958 and 1970 British birth cohort studies, we examine various biomarkers and self-reported measures of chronic disease by sibship size when respondents are aged in their mid-40s, mid-50s and mid-60s. We estimate separate linear probability models for each cohort, age and outcome, adjusting for childhood and early adulthood circumstances.

Results: We found no evidence of only children differing from those with one, two or three or more siblings, at any age, in any of the cohorts, on: heart problems, hypertension, high triglycerides, high glycated haemoglobin or high C-reactive protein. However, compared with only children, the probability for cancer (0.019, 95% confidence interval [CI]: 0.002, 0.035; age 46/1970) and poor general health (0.060, CI: 0.015, 0.127; age 55/1958; and 0.110, CI: 0.052, 0.168; age 63/1946) was higher among those with three or more siblings.

Conclusions: There is no consistent pattern of only child health disadvantage for midlife chronic disease outcomes across ages or cohorts in the UK. Research should focus on better understanding how sibship size differentials are contingent on context.

Background: Monitoring the incidence of chronic health conditions (CHCs) in childhood in England, using administrative data to derive numerators and denominators, is challenged by unmeasured migration. We used open and closed birth cohort designs to estimate the cumulative incidence of CHCs to age 16 years.

Methods: In closed cohorts, we identified all births in Hospital Episode Statistics (HES) from 2002/3 to 2011/12, followed to 2018/19 (maximum age 8 to 16 years), censoring on death, first non-England residence record or 16th birthday. Children must have linked to later HES records and/or the National Pupil Database, which provides information on all state school enrolments, to address unmeasured emigration. The cumulative incidence of CHCs was estimated to age 16 using diagnostic codes in HES inpatient records. We also explored temporal variation. Sensitivity analyses varied eligibility criteria. In open cohorts, we used HES data on all children from 2002/3 to 2018/19 and national statistics population denominators.

Results: In open and closed approaches, the cumulative incidence of ever having a CHC recorded before age 16 among children born in 2003/4 was 25% (21% to 32% in closed cohort sensitivity analyses). There was little temporal variation. At least 28% of children with any CHC had more than one body system affected by age 16. Multimorbidity rates rose with later cohorts.

Conclusions: Approximately one-quarter of children are affected by CHCs, but estimates vary depending on how the denominator is defined. More accurate estimation of the incidence of CHCs requires a dynamic population estimate.

Background: Before the COVID-19 pandemic, stagnating life expectancy trends were reported in some high-income countries (HICs). Despite previous evidence from country-specific studies, there is a lack of comparative research that provides a broader perspective and challenges existing assumptions. This study aims to examine longevity trends and patterns in six English-speaking countries (Australia, Canada, Ireland, New Zealand, United Kingdom, United States) by combining period and cohort perspectives and to compare them with other HICs.

Methods: Using data from the Human Mortality and World Health Organization Mortality Databases, we estimated partial life expectancy, lifespan inequality and cohort survival differences for 1970-2021, as well as the contribution of causes of death to the gap in life expectancy between English-speaking countries and the average for other HICs in 2017-19.

Results: In the pre-pandemic period, the increase in life expectancy slowed in all English-speaking countries, except Ireland, mainly due to stagnating or rising mortality at young-middle ages. Relative to other HICs, those born in Anglophone countries since the 1970s experienced relative survival disadvantage, largely attributable to injuries (mainly suicides) and substance-related mortality (mainly poisonings). In contrast, older cohorts enjoyed advantages for females in Australia and Canada and for males in all English-speaking countries except the United States.

Conclusions: Although future gains in life expectancy in wealthy societies will increasingly depend on reducing mortality at older ages, adverse health trends at younger ages are a cause for concern. This emerging and avoidable threat to health equity in English-speaking countries should be the focus of further research and policy action.

Background: Disease latency is defined as the time from disease initiation to disease diagnosis. Disease latency bias (DLB) can arise in epidemiological studies that examine latent outcomes, since the exact timing of the disease inception is unknown and might occur before exposure initiation, potentially leading to bias. Although DLB can affect epidemiological studies that examine different types of chronic disease (e.g. Alzheimer's disease, cancer etc), the manner by which DLB can introduce bias into these studies has not been previously elucidated. Information on the specific types of bias, and their structure, that can arise secondary to DLB is critical for researchers, to enable better understanding and control for DLB.

Development: Here we describe four scenarios by which DLB can introduce bias (through different structures) into epidemiological studies that address latent outcomes, using directed acyclic graphs (DAGs). We also discuss potential strategies to better understand, examine and control for DLB in these studies.

Application: Using causal diagrams, we show that disease latency bias can affect results of epidemiological studies through: (i) unmeasured confounding; (ii) reverse causality; (iii) selection bias; (iv) bias through a mediator.

Conclusion: Disease latency bias is an important bias that can affect a number of epidemiological studies that address latent outcomes. Causal diagrams can assist researchers better identify and control for this bias.